The Bayesian Modeling for Environmental Health Workshop is a two-day intensive course of seminars and hands-on analytical sessions to provide an approachable and practical overview of concepts, ...

An international research team has tested a hybrid control technique combining adapted perturb and observe (APO) with model-predictive control to address complex partial shading in solar arrays. The ...

In Table 3, the VIF values for each variable are < 5, which has been reduced as multicollinearity between variables. 3.3. Use the Entropy Weight Method to Weight the Data When exploring the factors ...

Above is a simulated charge sensor signal and its histogram. Below is a time integration that reduces noise and enables state identification (called threshold judgment, a conventional method). A ...

Landslide susceptibility assessment is crucial to mitigate the severe impacts of landslides. Although Bayesian network (BN) has been widely used in landslide susceptibility assessment, no study has ...

Proceedings of the National Academy of Sciences of the United States of America, Vol. 119, No. 11 (March 15, 2022), pp. 1-7 (7 pages) Artificial intelligence (AI) and machine learning models are being ...

This study proposes an important new approach to analyzing cell-count data that are often undersampled and cannot be correctly assessed with traditional statistical analyses. The presented case ...

In this paper, researchers from Queen Mary University of London, UK, University of Oxford, UK, Memorial University of Newfoundland, Canada, and Google DeepMind Moutain View, CA, USA proposed a ...

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...

Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...